The ALPL gene variant project: results of the first 100 reclassified variants
Bibliographic record
Abstract
Abstract Hypophosphatasia (HPP) is an inherited disorder that affects bone and tooth mineralization, among other body systems. HPP is caused by pathogenic variants in the alkaline phosphatase-liver (ALPL) gene, which encodes tissue nonspecific alkaline phosphatase. One major challenge in diagnosing HPP is interpreting variant of uncertain significance (VUS), which can create uncertainty for patients and healthcare professionals, leading to delays in diagnosis and treatment or incorrect diagnoses. Since February 2021, the ALPLgene variant consortium has reclassified 100 VUS using adjusted American College of Medical Genetics/Association for Molecular Pathology criteria. Of these, 11 were reclassified as pathogenic, 62 as likely pathogenic, three as likely benign, one as benign, and 23 remained as VUS; out of 100 variants, there were 81 missense, eight frameshifts, four in-frame deletions, two intronic, two synonymous, two nonsense, and one splice site variant. In vitrofunctional testing of the variant’s residual enzymatic activity and its dominant negative effect (DNE) was required for 40 variants.Out of 40 variants tested, 72% showed <30% residual activity and were reclassified as pathogenic or likely pathogenic. Among these, 48% exhibited a DNE. All variants with ˂15% residual activity showed a DNE, while those with over 20% did not. In terms of domains, all tested variants in the active site domain and 75% of those in the homodimeric interface showed <30% residual activity. The consortium’s reclassification of 100 ALPLvariants has resulted in a 21% increase in the number of variants in the Johannes Kepler University ALPLgene variant database. Furthermore, 136 new genotypes with 118 associated phenotypes, including asymptomatic states, have been added. These expanded resources will help improve genetic counseling for patients and families affected by ALPLvariants and enable faster diagnosis and medical decision-making.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".